Clinical Results of Long-Term Follow-Up of a Large, Active Surveillance Cohort With Localized Prostate Cancer
Bibliographic record
Abstract
PURPOSE We assessed the outcome of a watchful-waiting protocol with selective delayed intervention by using clinical prostate-specific antigen (PSA), or histologic progression as treatment indications for clinically localized prostate cancer. PATIENTS AND METHODS This was a prospective, single-arm, cohort study. Patients were managed with an initial expectant approach. Definitive intervention was offered to those patients with a PSA doubling time of less than 3 years, Gleason score progression (to 4 + 3 or greater), or unequivocal clinical progression. Survival analysis and Cox proportional hazard model were applied to the data. Results A total of 450 patients have been observed with active surveillance. Median follow-up was 6.8 years (range, 1 to 13 years). Overall survival was 78.6%. The 10-year prostate cancer actuarial survival was 97.2%. Overall, 30% of patients have been reclassified as higher risk and have been offered definitive therapy. Of 117 patients treated radically, the PSA failure rate was 50%, which was 13% of the total cohort. PSA doubling time of 3 years or less was associated with an 8.5-times higher risk of biochemical failure after definitive treatment compared with a doubling time of more than 3 years (P < .0001). The hazard ratio for nonprostate cancer to prostate cancer mortality was 18.6 at 10 years. CONCLUSION We observed a low rate of prostate cancer mortality. Among the patients who were reclassified as higher risk and who were treated, PSA failure was relatively common. Other-cause mortality accounted for almost all of the deaths. Additional studies are warranted to improve the identification of patients who harbor more aggressive disease despite favorable clinical parameters at diagnosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".